Additional file 5: of Representing and querying disease networks using graph databases

Cypher query on the relationships between a) the O15534 protein (PER gene) and b) the P20393 protein (REV/ERBalpha gene) and the core clock genes, (Table 3). (DOCX 77 kb

Additional file 4: of Representing and querying disease networks using graph databases

Information on genes related to a simple disease only, as reported in [23]. (DOCX 120 kb

Additional file 1: of Representing and querying disease networks using graph databases

Disease-associated genes used in the study (from [23]). (DOCX 93 kb

Additional file 3: of Representing and querying disease networks using graph databases

Brief introduction to Cypher query language; for more details on the Cypher language, the reader is referred to the Neo4j website: http://neo4j.com/ . (DOCX 17 kb

STON.pdf

<b>STON, SBGN to Neo4j: using graph database technologies for storing disease-relevant biological pathways and networks</b> <p> Vasundra Touré¹, Alexander Mazein², Dagmar Waltemath¹, Irina Balaur², Ron Henkel¹, Mansoor Saqi², Johann Pellet² and Charles Auffray²</p> <p> <br> </p> <p> ¹Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany.</p> <p> ²European Institute for Systems Biology and Medicine (EISBM), Centre National de la Recherche Scientifique (CNRS), Campus Charles Mérieux - Université de Lyon - 50 Avenue Tony Garnier, 69007 Lyon, France; IMI-eTRIKS consortium.</p> <p> <br> </p> <p> Abstract <br></p> <p> <br> </p> <p> <b>Background: </b>Graph databases can be successfully applied in Systems Biology and in Systems Medicine for managing extensive and complex information. Ultimately, graphs are a natural way of representing biological networks. The use of graph databases enables efficient storing and processing of biological relationships, and it can lead to a better response time when querying the data.</p> <p> <br> </p> <p> <b>Objectives: </b>We would like to use graph databases structure to store and explore biological pathways and networks.</p> <p> <br> </p> <p> <b>Method:</b> Translation rules have been determined to represent biological reaction networks in a graph model, that is to say as nodes, relationships and properties. The reaction networks are provided in the graphical standard Systems Biology Graphical Notation (SBGN). The graph model is stored in a Neo4j database.</p> <p> <br> </p> <p> <b>Results: </b>We present the Java-based framework STON (SBGN TO Neo4j) to import and translate metabolic, signalling and gene regulatory pathways. On the poster, we show examples of networks representing parts of the Asthma Map, the iNOS pathway (a SBGN use case network).</p> <p> <br> </p> <p> <b>Conclusion: </b>STON exploits the power of a graph database for the search in complex biological pathways. Importing biological pathways in a graph database enables:</p> <p> 1) identification of functional sub-modules and comparing different networks in order to discover common patterns. </p> <p> 2) merging multiple diagrams for creating large comprehensive networks for empowering systems medicine approaches.</p> <p> <br> </p> <p> <b>Availability:</b> The STON framework is available here: <a href="http://sourceforge.net/projects/ston/">http</a><a href="http://sourceforge.net/projects/ston/">://</a><a href="http://sourceforge.net/projects/ston/">sourceforge</a><a href="http://sourceforge.net/projects/ston/">.</a><a href="http://sourceforge.net/projects/ston/">net</a><a href="http://sourceforge.net/projects/ston/">/</a><a href="http://sourceforge.net/projects/ston/">projects</a><a href="http://sourceforge.net/projects/ston/">/</a><a href="http://sourceforge.net/projects/ston/">ston</a><a href="http://sourceforge.net/projects/ston/">/</a>.</p> <p><br> </p

Additional file 4 of STON: exploring biological pathways using the SBGN standard and graph databases

SBGN files in a COMBINE Archive. This COMBINE Archive contains the five SBGN-ML files used to generate the benchmark table present in the Additional file 1. (OMEX 181 kb

Reduced insulin secretion in M19-deficient INS-1 cells.

<p>(<b>A</b>) Northern blot analysis of the <i>M19</i> gene in human tissues. Pa: pancreas; Ki: kidney; Sk: skeletal muscle; Li: liver; Lu: lung; Pl: placenta; Br: brain; He: heart. Molecular markers are shown on the left. (<b>B</b>) Fluorescence microscopy of INS-1 cells double-labeled with the M19-specific P70612 antibody (M19, merge; green) and the MitoTracker dye (MitoTracker, merge; red). (<b>C</b>) Cell fractionation of INS-1 cells. Proteins of the total cell lysate (Lys), the cytosolic (Cyt) and the mitochondria (Mi) fractions were subjected to Western immunobloting. The cytosolic protein tubulin, the mitochondrial protein VDAC and M19 are detected. (<b>D</b>) INS-1 cells were transfected with a control pHYPER vector (sh control) or with the pHYPER vector encoding a M19-specific shRNA (sh M19). Western immunoblot analysis of the cell extracts shows expression levels of M19 and the control protein, tubulin. ATP production was determined in these cells (<b>E</b>), and insulin secretion was measured under basal glucose conditions (<b>F</b>). Results are the mean ± SEM of five (<b>E</b>), or four (<b>F</b>) independent experiments. (*) indicates statistical significance at p<0.05.</p

Identification of a mitochondrial targeting signal.

<p>(<b>A</b>) Prediction of the secondary structure of mouse M19 (<i>Mus musculus</i> NM026063) using 4 different algorithms: phyre, PSIPRED, SAM and jufo. The predicted α-helices are indicated by black lines along the amino-acid sequence. (<b>B</b>) Helical wheel presentation of the N-terminal α-helix of mouse M19, from amino acid 1 to 13. Hydrophobic residues are indicated in black circles while the positively charged amino acids are mentioned with a “+”. The first methionine (amino acid 1), at the top of the figure, is considered as a positively charged residue. (<b>C</b>, <b>D</b>) C2C12 myoblasts were transfected with the pQETriSystem vector encoding histidine-tagged M19 (<b>C</b>) or a histidine-tagged M19 mutant lacking amino acids 1 to 12 (<b>D</b>). Indirect immunofluorescence was performed using an anti-histidine antibody. (<b>E</b>–<b>J</b>) C2C12 myoblasts were transfected with the pEGFP-N1 vector encoding GFP alone (<b>E</b>, <b>F</b>), the pEGFP-N1 vector encoding the N-terminal M19 α-helix fused to the N-terminal end of GFP (<b>G</b>, <b>H</b>), and the PEGFP-C3 vector encoding the N-terminal M19 α-helix coupled to the C-terminal end of GFP (<b>I</b>, <b>J</b>). Fluorescence microscopy allows the direct detection of GFP constructs (<b>E</b>, <b>G</b>, <b>I; green</b>) and the indirect detection of cytochrome c using an anti-cytochrome c antibody (<b>F</b>, <b>H</b>, <b>J; red</b>).</p

Expression of late muscle differentiation markers is affected in differentiated M19-deficient C2C12 cells.

<p>(<b>A</b>, <b>B</b>) C2C12 myoblasts were transfected with a control siRNA (si control) or a M19-specific siRNA (si M19) and were then placed in differentiation medium for 7 days. Protein extracts from transfected cells grown in proliferation medium (d0) or in differentiation-promoting conditions for 3, 5 and 7 days (d3, d5, d7) were analyzed by Western immunobloting using the M19-specific P70612 antibody (<b>A</b>) and a MHCII antibody (<b>B</b>). Densitometry analysis of the detected bands is presented as the relative expression of M19 (<b>A</b>) and MHCII (<b>B</b>) normalized to tubulin. Results are the mean ± SEM of three independent experiments. (*) and (**) indicate statistical significance at p<0.05 and at p<0.01. In a similar experiment, C2C12 myoblasts were transfected with the M19-specific shRNA vector allowing the expression of the specific shRNA with GFP. Cells were placed in differentiation medium for 7 days. Fluorescence microscopy allows the direct visualization of GFP-labeled cells expressing the M19-specific shRNA (<b>C, merge; green</b>) and the detection of MHCII using an anti-MHCII antibody (<b>D, merge; red</b>). (<b>E</b>) Protein extracts from control shRNA-transfected C2C12 cells (sh control) and M19-specific shRNA-transfected C2C12 cells (sh M19) grown in differentiation-promoting conditions for 7 days were analyzed by Western immunoblotting. The expression of the late muscle differentiation markers α-actinin 2, troponin T, MHCI and MHCII is shown, as well as the control protein tubulin.</p

Expression and localization of M19 in muscle cells.

<p>(<b>A</b>) Coomassie-blue stained gel and Western blot analysis of M19 in extracts from C2C12 cells grown in proliferation medium (d0) or placed in differentiation-promoting conditions for 2 to 9 days (d2 to d9). M19 is detected by the rabbit polyclonal P70612 antibody. (<b>B</b>, <b>C</b>) C2C12 myoblasts were grown in proliferation medium or (<b>D</b>, <b>E</b>) were placed in differentiation medium for 6 days, and then were double-labeled with the specific P70612 antibody (<b>B</b>, <b>D; green</b>) and an anti-cytochrome c antibody (<b>C</b>, <b>E; red</b>). There is a co-localization between the 2 detected proteins in C2C12 myoblasts (<b>B</b>, <b>C, merge</b>) and myotubes (<b>D</b>, <b>E, merge</b>) as indicated by arrowheads. (<b>F</b>, <b>G</b>) Double-label indirect immunofluorescence of mouse <i>Tibialis anterior</i> sections showing M19 (<b>F; green</b>) and cytochrome c (<b>G; red</b>). (<b>H</b>) After C2C12 cell fractionation, proteins from the cytosolic and the mitochondria fractions were separated by SDS-PAGE. Tubulin, COX IV and M19 are detected by Western immunobloting. (<b>I</b>) Purified mitochondria are subjected to limited degradation using increasing concentration of trypsin, from 0 to 80 µg/ml. The mitochondria are then lysed in Laemmli buffer. Tom40 and M19 are detected by Western immunobloting. (<b>J</b>) Purified mitochondria are disrupted with freeze/thaw cycles, followed by Na₂CO₃ precipitation. After centrifugation, the membrane fraction (memb) and the matrix/intermembrane space fraction (matrix) are analyzed by Western immunobloting using a VDAC antibody and the P70612 antibody.</p